Average Utility Research Articles

Incentive program to strengthen motivation for increasing physical activity via conjoint analysis.

Objectives Promoting physical activity is a key public health issue. Incentive programs have attracted attention as a technique for promoting physical activity. For the use of effective incentives, there is a need to clarify the most effective incentive program conditions for the promotion of physical activity. Therefore, the present study used the conjoint analysis to examine the effective incentive program conditions for strengthening the motivation to increase physical activity.Methods Data on 1,998 subjects (aged 40-74) were analyzed. The main variables in this study were physical activity (IPAQ-Short Form) and the strengthening of motivation to increase physical activity. The incentive programs that were implemented, comprised four factors: 1) cash equivalents (1,000 yen, 2,000 yen, and 3,000 yen); 2) duration between increase in physical activity and receipt of the incentive (1, 2, or 3 months); 3) method to record the physical activity (recording sheet, recording website, and automatic pedometer recording); and 4) lottery (yes or no). Eleven incentive programs were created, which was the minimum number required for comparison of these factors and levels. The average importance of each of the four factors was calculated to compare their contributions to the strengthening of the motivation to increase physical activity. The utility of each level was also calculated to compare their contributions to the strengthening of motivation. All statistics were stratified by age (≤65 years and 65+ years) and physical activity (<150 min/week, 150+ min/week) for additional analysis.Results Cash incentives and the lottery ranked equally on average importance, followed by duration and recording methods. Utility was higher for each factor, as follows: 1) more valuable cash incentives, 2) shorter duration, 3) automatic pedometer recording, and 4) no lottery. There was no notable difference in the average importance and utility of age and physical activity.Conclusions The results of this study suggest that no lottery and more valuable incentives were important for improving the effectiveness of incentive programs in increasing physical activity. Moreover, these two factors would be important regardless of age and physical activity levels. Further intervention studies on incentive programs for increasing physical activity considering the present results are needed.

Max‐utility resource allocation for indoor small cell networks

The development of indoor small cell provides network operators with new opportunities to address surging mobile data traffic, coverage infill and capacity boost scenarios, and finally results in growing expectations relative to quality of experience (QoE). However, the deployment of indoor small cell base station also raises some resource allocation issues. This study aims to propose an max-utility resource allocation mechanism that maximises all users’ utility for indoor small cell networks. The objective of the proposed max-utility resource allocation algorithm is to optimise the total user's QoE while guaranteeing as many as possible users can enjoy their request service at an acceptable quality. This is achieved by considering user's QoE state and signal strength into the resource allocation algorithm. Multiservice scenario is also considered in the proposed max-utility resource allocation algorithm. To compare the performance of the proposed max-utility resource allocation mechanism with round-robin, max-throughput and max-minMOS approach, a simulation analysis is implemented. The simulation result showed that the proposed strategy achieves the best average utility compared with other approaches. Result also showed that the proposed strategy is suitable for indoor small cell networks under various kinds of scenarios with different user behaviours and network topologies.

Assessment of patient's and health professional's experience of integrated care: preliminary results from a pilot survey in Veneto Region-Italy

Assessment of patient's and health professional's experience of integrated care: preliminary results from a pilot survey in Veneto Region-Italy

Sense and sensibility – The utility of HVAC sensors for large zones

Utility of deploying environment/occupancy sensors in buildings is well studied. However, the settings in the existing works are limited in scope and hence the observations may not be generalizable. This paper proposes an approach to quantify the utility of sensing in generic zone setups. The usefulness of sensing temperature and occupancy is quantified in terms of ‘information-utility’ and ‘actuation-utility’. The information-utility is quantified as the minimum number of sensors required to reconstruct the ground truth within a tolerable error; and the actuation-utility is the energy savings due to sensor deployment from a baseline, subject to acceptable occupant comfort. A thermal model based on thermodynamic principles is used to model the zone responses while quantifying the sensing utility.The approach is evaluated through data from a real-world office building. Key findings include: (1) sensing population accurately requires higher number of sensors than sensing temperature. (2) Under steady-state, maximum actuation-utility of sensing at finer spatial resolutions increases with number of actuators. (3) For a real-world case, the maximum actuation-utility was ∼30%. After accounting for system inertia, the maximum and average actuation-utility of sensing were 22% and 5% respectively. This suggests that frequently occurring occupancy patterns influence the average utility of finer-sensing.

Health Utility of Early Hemiarthroplasty vs Delayed Total Hip Arthroplasty for Displaced Femoral Neck Fracture in Elderly Patients: A Markov Model

BackgroundTreatment for femoral neck fracture among patients aged 65 years or older varies, with many surgeons preferring hemiarthroplasty (HA) over total hip arthroplasty (THA). There is evidence that THA may lead to better functional outcomes, although it also carries greater risk of mortality and dislocation rates. MethodsWe created a Markov decision model to examine the expected health utility for older patients with femoral neck fracture treated with early HA (performed within 48 hours) vs delayed THA (performed after 48 hours). Model inputs were derived from the literature. Health utilities were derived from previously fit patients aged more than 60 years. Sensitivity analyses on mortality and dislocation rates were conducted to examine the effect of uncertainty in the model parameters. ResultsIn the base case, the average cumulative utility over 2 years was 0.895 for HA and 0.994 for THA. In sensitivity analyses, THA was preferred over HA until THA 30-day and 1-year mortality rates were increased to 1.3× the base case rates. THA was preferred over HA until the health utility for HA reached 98% that of THA. THA remained the preferred strategy when increasing the cumulative incidence of dislocation among THA patients from a base case of 4.4% up to 26.1%. ConclusionWe found that delayed THA provides greater health utility than early HA for older patients with femoral neck fracture, despite the increased 30-day and 1-year mortality associated with delayed surgery. Future studies should examine the cost-effectiveness of THA for femoral neck fracture.

QoE-Aware Power Management in Vehicle-to-Grid Networks: A Matching-Theoretic Approach

Frequency, time, and places of charging and discharging have critical impact on the quality of experience (QoE) of using electric vehicles (EVs). EV charging and discharging scheduling schemes should consider both the QoE of using EV and the load capacity of the power grid. In this paper, we design a traveling plan-aware scheduling scheme for EV charging in driving pattern and a cooperative EV charging and discharging scheme in parking pattern to improve the QoE of using EV and enhance the reliability of the power grid. For traveling plan-aware scheduling, the assignment of EVs to charging stations is modeled as a many-to-one matching game and the stable matching algorithm (SMA) is proposed. For cooperative EV charging and discharging in parking pattern, the electricity exchange between charging EVs and discharging EVs in the same parking lot is formulated as a many-to-many matching model with ties, and we develop the Pareto optimal matching algorithm (POMA). Simulation results indicates that the SMA can significantly improve the average system utility for EV charging in driving pattern, and the POMA can increase the amount of electricity offloaded from the grid which is helpful to enhance the reliability of the power grid.

PHP95 - How Much are Chinese Willing to Pay for the Health Improvement?

Estimate the willingness to pay value for the health improvement of the general Chinese using contingent valuation method. And comparing the difference of results between on-line and face-to-face survey. Two widely used preference-based health-related quality of life instruments were used to elicit utility. Firstly, the respondents were requested to evaluate their own health states with the instruments of VAS and EQ-5D. Secondly, collected the respondents’ WTP for obtaining an improvement in health from their own health state to the perfect health state, using an open ended method. Finally, we collected the social-demographic characteristics of the respondents. We randomly sampled 97 respondents in total. Among them, 61 were from an on-line panel and 36 were from face-to-face survey in July 2015. The average utility of subject’s own health were 0.96 and 0.87, based VAS and EQ-5D respectively. With the EQ-5D instrument, more than 70% (68/97) of the respondents thought the utility of their own health were 1, namely the perfect health state. For those respondents, the health improvement were zero, so the willingness to pay for health improvement cannot be estimated. On the other hand, the social-demographic characteristics in on-line and face-to-face survey showed no difference except the age characteristic. It is not a good idea in China to estimate the respondents’ willingness to pay for the health improvement that from their own health states to the perfect health state. We should try to explore other methods to express the health improvement, for example, assume that the respondents in a not perfect health state. We also conclude that the respondents in on-line survey were younger than the face-to-face survey. So we suggest that on-line and face-to-face survey can be used in the same time to ensure the respondents were representative.

PCV38 - A Systematic Review of Cardiovascular Event Utilities in Asia

This systematic literature review (SLR) aimed to identify and evaluate utilities reported for stroke, acute coronary syndrome (ACS), and heart failure in Asia. A SLR was conducted to identify English-language articles in Embase, PubMed, and the grey literature published between 1992 and August 2015 using keywords for cardiovascular (CV) events and utilities. Primary studies reporting utilities for stroke, ACS (including myocardial infarction and angina), and heart failure in adults were included. Utilities were evaluated by population, health state, and methodology. Twenty-three articles reported on studies in Asia, including South Korea (8), China (5), Thailand (3), Taiwan (2), India, Japan, Malaysia, Singapore, and Vietnam (1 each). Nearly all studies (20/23) reported EQ-5D utilities and only two used direct methods of elicitation; all utilities were elicited from patients experiencing the conditions rather than general population respondents. Seventeen studies reported utility values for stroke, 12 studies for ACS, and no studies reported on heart failure. Average utilities ranged widely for stroke (-1.99–0.96) and ACS (0.11–1). These wide ranges were seen with most methods of elicitation (EQ-5D [n=20]: -0.14–1; standard gamble [n=3]: -1.99–0.72; HUI-3 [n=1]: -0.23–0.62). SF-6D range was narrow (0.68–0.69) with all values from the same ACS population (n=3 papers). In stroke, severe disease was associated with lower utility values (-1.57–0.49; n=3) than mild disease (0.62 to 0.96; n=4); disease severity was not reported for ACS. This SLR identified a wide range of utility values for stroke and ACS in Asia. Method of elicitation and severity of disease may impact utility values. Substantial data gaps were observed, particularly for heart failure, levels of disease severity for ACS, and direct methods of utility elicitation; further study is needed to determine whether data from outside Asia can be used to fill such gaps.

Efficient Upstream Bandwidth Multiplexing for Cloud Video Recording Services

The upsurge of cloud video recording (CVR) has gained increasing attention from the general public and entrepreneurs. With live video records archived in the cloud, the CVR paradigm enables various smart services by keeping track of activities in the monitored region from anywhere at any time. However, the limited upstream bandwidth affects the quality of surveillance when multiple distributed cameras share the same upstream link. To solve the problem, this paper proposes an efficient upstream bandwidth multiplexing algorithm to intelligently allocate upstream bandwidth for each live video stream while maximizing the overall utility from the perspective of a CVR user. Specifically, we formulate the upstream bandwidth multiplexing problem as a constrained stochastic optimization problem, and apply the technique of hierarchical approximation to solve it efficiently. Our algorithm can be extended to take the priority of video streams into account and allocate more upstream bandwidth to video streams with higher priorities. We explicitly prove the approximation ratio of the proposed algorithm. In addition, we also conduct extensive trace-driven simulations to verify the effectiveness of our algorithm. The simulation results show that our algorithm improves the overall CVR user utility by over 20% compared with other alternatives, and the average utility per bandwidth unit is guaranteed to be stable even when the number of video streams increases.

Economic and Health-Related Quality of Life Outcomes of Whiplash Associated Disorders

This study examines the links between severity of whiplash associated disorder and costs and health outcomes. The study aims to estimate the economic costs and health-state utilities associated with disability levels and recovery trajectories after acute whiplash injury. Data used were from the Managing Injuries of the Neck Trial, which collected information on 3851 people over a 12-month period after acute whiplash injury. Effects of whiplash associated disorder severity on economic costs (measured from a societal perspective and separately from a health and personal social services perspective) were estimated using two-part regression models, comprising probability of incurring a cost and the total cost, given one was incurred. Effects on health-state utilities (measured using the EQ-5D and SF-6D) were estimated using ordinary least squares regression, and two-part models as for costs. There was a direct relationship between severity of disability after acute whiplash injury and economic costs. Between baseline and 4 months, average societal costs for those with no disability were £99.55 (UK£, 2009 prices), increasing to £668.53 for those with complete disability. Average societal costs for the whole sample were £234.15 over the first 4 months, decreasing to £127.51 between 8 and 12 months. Conversely, utility scores decreased with increased disability. The average EQ-5D utility score was 0.934 at 4 months for those with no disability, decreasing to 0.033 for those with complete disability. The average EQ-5D utility score for the whole sample increased from 0.587 immediately post-injury to 0.817 at 12 months. Relative costs and disutilities generated by the multivariate models are also presented by disability level and recovery trajectory. These results provide estimates of the costs and health-state utilities associated with disability levels and recovery trajectories after acute whiplash injury. They can be used to inform estimates of the cost-effectiveness of interventions targeting whiplash-associated disorders. 3.

A distributed algorithm for maximizing utility of data collection in a crowd sensing system

Mobile crowd sensing harnesses the data sensing capability of individual smartphones, underpinning a variety of valuable knowledge discovery, environment monitoring, and decision-making applications. It is a central issue for a mobile crowd sensing system to maximize the utility of sensing data collection at a given cost of resource consumption at each smartphone. However, it is particularly challenging. On the one hand, the utility of sensing data from a smartphone is usually dependent on its context which is random and varies over time. On the other hand, because of the marginal effect, the sensing decision of a smartphone is also dependent on decisions of other smartphones. Little work has explored the utility maximization problem of sensing data collection. This article proposes a distributed algorithm for maximizing the utility of sensing data collection when the smartphone cost is constrained. The design of the algorithm is inspired by stochastic network optimization technique and distributed correlated scheduling. It does not require any prior knowledge of smartphone contexts in the future, and hence sensing decisions can be made by individual smartphone. Rigorous theoretical analysis shows that the proposed algorithm can achieve a time average utility that is within O(1/ V) of the theoretical optimum.

A novel hybrid medium access control protocol for inter-M2M communications

A scalable medium access control (MAC) protocol is crucial for machine-type devices to access the channel simultaneously in a machine-to-machine (M2M) network. There can be two types of scenarios in an M2M network. First, where the M2M devices communicate with the base station one-by-one, and second, where the M2M devices directly communicate with each other within a group or cluster without any human intervention (Inter-M2M communication). Considering the second type of scenario, the devices can use basic contention or reservation-based MAC protocols. But with such a large number of M2M devices, adaptability, and scalability become bottlenecks. Therefore, in this paper, we propose a novel scalable hybrid-MAC protocol, which combines the benefits of both contention-based and reservation-based medium access schemes. We assume that the contention and reservation portion of M2M devices is a frame structure, which mainly has two parts: contention interval (CI) and data transmission interval (DTI). The devices contend for the channel access during CI. After contention, the successful devices win time-slots and transmit data packets during DTI. In our proposed hybrid-MAC scheme, each M2M device is IEEE 802.11 DCF enabled, and within each time slot during DTI, the devices share data with each other. The analytical and simulation results show that the proposed hybrid-MAC protocol performs better than slotted-ALOHA, p-persistent CSMA, and TDMA in terms of aggregate throughput, average transmission delay, channel utility, and energy consumption.

Study and Simulation on Dynamics of a Risk-Averse Supply Chain Pricing Model with Dual-Channel and Incomplete Information

Under the industrial background of dual-channel, volatility in demand of consumers, we use the theory of bifurcations and numerical simulation tools to investigate the dynamic pricing game in a dual-channel supply chain with risk-averse behavior and incomplete information. Due to volatility of demand of consumers, we consider all the players in the supply chain are risk-averse. We assume there exist Bertrand game and Manufacturers’ Stackelberg in the chain which are closer to reality. The main objective of the paper is to investigate the complex influence of the decision parameters such as wholesale price adjustment speed, risk preference and service value on stability of the risk-averse supply chain and average utilities of all the players. We lay emphasis on the influence of chaos on average utilities of all the players which did not appear in previous studies. The dynamic phenomena, such as the bifurcation, chaos and sensitivity to initial values are analyzed by 2D bifurcation phase portraits, Double Largest Lyapunov exponent, basins of attraction and so on. The study shows that the manufacturers should slow down their wholesale price adjustment speed to get more utilities, if the manufacturers are willing to take on more risk, they will get more profits, but they must keep their wholesale prices in a certain range in order to maintain the market stability.

SLA based cloud service composition using genetic algorithm

Cloud computing tends to provide high quality on-demand services to the users. Numerous services are evolving today. Functionally similar services are having different non-functional properties such as reliability, availability, accessibility, response time and cost. A single service is inadequate for constructing the business process. Such business process is modeled as composite service. Composite service consists of several atomic services connected by workflow patterns. Selecting services for service composition with the constraints specified in Service Level Agreement is the NP-hard problem. Such a cloud service composition problem is modeled in this paper. Genetic based cloud service composition algorithm (GCSC) is proposed. Proposed algorithm is compared with the existing genetic based cloud service composition algorithm based on average utility rate and convergence time. It is proved that the proposed algorithm provides better performance as compared to the existing cloud service composition algorithm.

Opportunistic WiFi Offloading in Vehicular Environment: A Game-Theory Approach

In this paper, we study opportunistic traffic offloading in a vehicular environment, where the cellular traffic of vehicular users (VUs) is offloaded through carrier-WiFi networks deployed by the mobile network operator (MNO). By jointly considering users' satisfaction, the offloading performance, and the MNO's revenue, two WiFi offloading mechanisms are proposed: auction game-based offloading (AGO) and congestion game-based offloading (CGO). Moreover, we introduce an approach to predict WiFi offloading potential and access cost and incorporate it in the offloading mechanisms. Specifically, with the AGO mechanism, the MNO employs auctions to sell WiFi access opportunities; VUs decide whether to bid according to their utilities and are capable of using WiFi if the auction is won. With the CGO mechanism, a VU calculates utility considering other VUs' strategies and makes offloading decisions accordingly. We show that the AGO mechanism can maximize social welfare and increase the MNO's revenue, whereas the CGO mechanism can achieve a better performance of average VU utility and fairness. Additionally, both AGO and CGO mechanisms can improve the overall WiFi offloading performance. Through simulations, we demonstrate that both AGO and CGO mechanisms can achieve higher average utility of VUs and lower average service delay and offload much more cellular traffic compared with existing offloading mechanisms.

Economic Evaluation of Treatments for Pediatric Bilateral Severe to Profound Sensorineural Hearing Loss: An Australian Perspective.

In Australia, surgical treatment options for children with bilateral severe to profound sensorineural hearing loss exist in a continuum ranging from unilateral cochlear implantation (CI), sequential bilateral CI through to simultaneous bilateral CI, depending on the condition. When treatment options are mutually exclusive, the mean costs and benefits of each treatment group are summed together to obtain the total mean costs and benefits. This enables an incremental analysis of treatment options in the context of the treated populations.The objective was to evaluate the cost-utility of current Australian CI treatment practices in children using domestic costs and consequences when compared with bilateral hearing aids (HAs). Economic evaluation including a Markov model based on secondary sources. The base case modeled a government health payer perspective over a child's lifetime. Primary and secondary school education costs were also assessed. Bilateral HAs compared with CI, including unilateral, sequential bilateral, or simultaneous bilateral CI weighted according to treatment. Incremental costs per quality adjusted life year. Approximately 42% of children in Australia with unilateral CI did not transition to sequential bilateral nor undergo simultaneous bilateral implantation. This differs from previous economic evaluations that assumed 100% of children transitioned to sequential bilateral CI treatment or were treated with simultaneous bilateral CI.The incremental cost utility of unilateral cochlear implantation compared with HAs was AUD 21,947/QALY. The weighted average incremental cost utility of the combined cochlear implantation treatment groups was AUD 31,238/QALY when compared with HAs. Previous economic evaluations of cochlear implantation assumed 100% of unilaterally treated patients would transition to sequential bilateral or be treated with simultaneous bilateral implantation. This approach does not take into account the total treated population, where a proportion of patients are treated with unilateral CI.CI was cost effective when compared with HAs, and included children treated with unilateral, sequential bilateral, and simultaneous bilateral CI.The model was sensitive to the number of assessment and habilitation visits. Alternative health service models with cost efficiencies are needed to reduce after care costs.

Cooperative Energy Broadcasting System With Massive MIMO

Different from information transmission, inter-cell interference benefits energy harvesting of energy users (EUs) in multi-cell scenario. Therefore, the objective of this letter is to maximize the average energy harvesting utility of multiple EUs by leveraging inter-cell cooperation. Considering channel state information (CSI) delay, a cooperative energy precoder with centralized implementation is first proposed when the energy stations (ESs) employ massive multiple-input multiple-output. Then, its distributed implementation is presented in terms of a local constraint at each ES and information exchange among ESs. Results indicate that the cooperative energy transfer significantly outperforms the non-cooperative energy transfer with either perfect or delay CSI, and the proposed energy precoder with proportional fairness utility can balance the harvested energy and fairness among different EUs.

Economic Analysis of Deep Brain Stimulation in Parkinson Disease: Systematic Review of the Literature

Parkinson disease (PD) is a chronic multifaceted neurodegenerative disorder of adult onset that affects quality of life and places a burden on patients, caregivers, and society. In early disease, dopaminergic therapy improves motor symptoms, but as the disease progresses, symptoms tend to increase in frequency and severity, even with best medical treatment (BMT). Deep brain stimulation (DBS) becomes an option for certain patients, but cost becomes an important issue. We performed a systematic review of the literature of economic studies of the use of DBS in patients with PD, including costs studies or economic evaluations expressed as cost per improvement in quality life, decrease in dose of pharmacological treatments, and the decrease of caregiver burden. We reviewed the following databases: Medline/PubMed, Embase, Cochrane Database of Systematic Reviews, LILACS, Cochrane Central Register of Controlled Trials, WHO International Clinical Trials Registry Platform ICTRP portal and ClinicalTrials.gov from 1980 to 2015. Costs have been converted or adjusted to 2016 US dollars (US$). Nine studies were identified. The average cost of DBS for a patient with PD in 5 years is US$186,244. The quality-adjusted life year was higher in DBS compared with BMT after at least 2 years of treatment, with an average incremental cost utility ratio of US$41,932 per additional quality-adjusted life year gained. Costs in the first year are higher with DBS because of direct costs related to the surgical procedure, the device, and the more frequent controls. Studies show better results with a longer time horizon (up to 5 years). DBS is a cost-effective intervention for patients with advanced PD, but it has a high initial cost compared with BMT. However, DBS reduces pharmacologic treatment costs and should also reduce direct, indirect, and social costs of PD on the long term.

Optimal markdown policy of perishable food under the consumer price fairness perception

Markdown policies are widely used by retailers to sell perishable food. Consumers purchase food at different prices during different sales periods. Some consumers may compare their experience with others who purchase the same items. Price unfairness or inequity is perceived when different prices are quoted without reasonable explanations. This study develops an optimal markdown model for perishable food pricing to optimise the food retailer revenue and enable a maximum aggregated consumer utility considering individuals’ price fairness perception. The model serves as the first step in evaluating trade-offs between food retailer revenue and consumer utility. In addition, it enables consumer utility to be depicted through perceived price fairness by including the effects of food perishability and scarcity. Another innovative feature is the equalisation of the consumer average aggregated utility during different sales periods as a condition of intertemporal price fairness perception. The proposed model is compared with two benchmark models to justify the effectiveness and advantages in the example. Finally, a sensitive analysis based on the food deterioration rate, consumer food desire rate and consumer average reservation price is conducted to justify the manner in which these factors influence the optimal pricing policy, and managerial insights are suggested for food retailers.

Mining recent high average utility patterns based on sliding window from stream data

Utility pattern mining is a technique that finds valuable patterns from large-sized databases with each item’s importance and quantity information associated with it. The representative utility pattern mining technique, high utility pattern mining (HUPM), calculates the utilities of patterns by sum mating all of the item utilities in the patterns. However, such utility measures for patterns in HUPM have a drawback in whichpatterns with long lengths tend to have utilities sufficient to become high utility patterns. For these reasons, high average utility pattern mining (HAUPM) employing different utility measures has been studied in order to consider such pattern length factors. Recently, techniques for handling stream data are necessary because many data sources, e.g. sensors and POS devices, produce data in real time. However, all the existing HAUPM algorithms are unable to find up-to-date, meaningful patterns over data streams. We thus propose the first sliding window based HAUPM algorithm discovering recent high average utility patterns over data streams. Based on the sliding window model, our algorithm divides stream data into numerous batches, and keeps only recent batches in its window. Thereby, the algorithm can mine recent, important patterns over data streams. We also introduce a new strategy that enhances the performance of our algorithm by minimizing the overestimated average utilities stored in the proposed data structure. The experimental results show that our algorithm outperforms the competitors.